With matched-scale sparse autoencoders, HuBERT-ECG best preserves its ECG representation while ECG-JEPA best exposes clinical measurements through single features — a leader split that repeats on MIMIC-IV-ECG.
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ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders
With matched-scale sparse autoencoders, HuBERT-ECG best preserves its ECG representation while ECG-JEPA best exposes clinical measurements through single features — a leader split that repeats on MIMIC-IV-ECG.